https://github.com/VICO-UoE/L2I
공식 코드Learning to Impute: A General Framework for Semi-supervised Learning
Papers with Code 아카이브
Facial Recognition and Modelling
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Varat7v2/adaptive-threshold
공식 코드Adaptive Threshold for Online Object Recognition and Re-identification Tasks
https://github.com/VinAIResearch/blur-kernel-space-exploring
공식 코드https://github.com/WakingHours-GitHub/EPL
공식 코드https://github.com/Wayfear/Autotune
공식 코드Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
https://github.com/Weizhi-Zhong/IP_LAP
공식 코드Identity-Preserving Talking Face Generation with Landmark and Appearance Priors
https://github.com/WillHawkins3/deepfakesondemand
공식 코드Deepfakes on Demand: the rise of accessible non-consensual deepfake image generators
https://github.com/WindQingYang/PipeNet
공식 코드PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing
https://github.com/X-zhangyang/Real-World-Masked-Face-Dataset
공식 코드https://github.com/XiaohangZhan/cdp
공식 코드Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/XuyangSHEN/Pairwise-GAN
공식 코드Pairwise-GAN: Pose-based View Synthesis through Pair-Wise Training
https://github.com/YZY-stack/DF40
공식 코드https://github.com/YaN9-Y/lafin
공식 코드https://github.com/YadiraF/DECA
공식 코드Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
https://github.com/YadiraF/PIXIE
공식 코드Collaborative Regression of Expressive Bodies using Moderation
https://github.com/YadiraF/PRNet
공식 코드Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
https://github.com/YangNaruto/FQ-GAN
공식 코드https://github.com/YantaoShen/openBCT
공식 코드https://github.com/YonghaoHe/A-Light-and-Fast-Face-Detector-for-Edge-Devices
공식 코드https://github.com/YoushanZhang/Adversarial-Regression-Learning-for-Bone-Age-Estimation
공식 코드https://github.com/YuYin1/DA-GAN
공식 코드https://github.com/YudongGuo/AD-NeRF
공식 코드AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis
https://github.com/Yushgoel/AdversarialAttack
공식 코드https://github.com/Yuto-Matsunaga/Prompt_Tuning_for_Audio_Deepfake_Detection
공식 코드https://github.com/YuvalNirkin/fsgan
공식 코드https://github.com/ZEISS/iPad_TrueDepth_Issue_App
공식 코드On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad Generations
https://github.com/ZEISS/iPad_TrueDepth_Issue_Eval
공식 코드On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad Generations
https://github.com/ZJU-Brain/OTFPF
공식 코드https://github.com/ZLeopard/PEDCC-Loss
공식 코드A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids
https://github.com/ZamDimon/liveness-detection
공식 코드Cross-Database Liveness Detection: Insights from Comparative Biometric Analysis
https://github.com/ZhaoJ9014/High_Performance_Face_Recognition
공식 코드https://github.com/ZhaoJ9014/face.evoLVe.PyTorch
공식 코드https://github.com/ZhaoxuanWu/Trusted-Maximizers-Entropy-Search-BO
공식 코드Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization
https://github.com/Zheng222/DMFN
공식 코드https://github.com/ZhenghLi/Automated-Detection-of-Equine-Facial-Action-Units
공식 코드https://github.com/ZhiwenShao/ADLD
공식 코드Unconstrained Facial Action Unit Detection via Latent Feature Domain
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.